Implementation of a calibrated Urban Building Energy Model (UBEM) for the evaluation of energy efficiency scenarios in a Kuwaiti residential neighborhood

To support the implementation of urban energy efficiency strategies, a new generation of urban building energy modeling (UBEM) tools has been introduced which allows cities to simulate the expected energy demands of neighborhoods. In order to define simulation inputs, UBEM models usually use archetypes, in which occupant-related parameters like occupancy, plug loads or set point temperatures are defined deterministically. This simplification can lead to wrong predictions in savings for energy efficiency strategies. Building on previous research, this paper implements an UBEM workflow to evaluate the relevance of occupant uncertainty modeling when predicting energy efficiency savings for a neighborhood. An existing model of 172 villas in Kuwait city is used as a case study. Occupant parameters are characterized through both deterministic assumptions and calibrated uncertainty distributions. Three retrofit and two pricing scenarios are modeled and simulated using both methods. Finally, energy and cost savings are calculated, and the performance of both modeling methods is evaluated from the application perspectives of three urban decision makers. Results show that while effective for aggregate savings, deterministic UBEMs ignore uncertainties up to 30% when considering single buildings, and can misrepresent average cost savings, especially with tiered pricing.